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PubMed · 12886724

Pick and choose. Selecting billing and scheduling software.

Christina Moschella·Genna Gretsky
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Abstract

HIPAA's regulations are spurring many medical groups to change their billing and/or scheduling software. Here is a step-by-step process to evaluate your practice's needs, find a vendor and figure the time the process will take. Checklists can assist you at each stage of the process.

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Appointments and SchedulesDecision Making, OrganizationalGroup PracticePatient Credit and CollectionSoftwareUnited StatesJournal Article

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Christina Moschella, Genna Gretsky. 2003. Pick and choose. Selecting billing and scheduling software.. https://pubmed.ncbi.nlm.nih.gov/12886724/

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PubMed2007

Computer modeling of patient flow in a pediatric emergency department using discrete event simulation.

UNLABELLED: Increasing patient census and department overcrowding are universal concerns in pediatric emergency medicine. Accurate predictions of patient flow and resource utilization in the pediatric emergency department (PED) are important in determining what aspects of PED activity could be modified to improve patient flow, reduce patient waiting times, and increase staff efficiency and morale, and thus direct change more effectively. BACKGROUND: We report (1) the construction of a Patient Flow Model (PFM) using discrete event simulation to test simulated PED staffing scenarios that were designed to alleviate the pressures that result from increased census and overcrowding, and (2) a Physician Scheduling Analysis Tool to assist in physician scheduling. METHODS: Arena discrete event simulation modeling software was used to develop a model of PED patient flow after extensive interviews with PED staff and direct observation of patient flow in July 2005. A total of 517 patients were directly observed, and all modeled aspects of their interaction with PED staff and resources were recorded. Historical demographic patient arrival information was combined with observed patient flow data to provide simulated patient arrival rates for the PFM and was also used to construct the Physician Scheduling Analysis Tool. Validation of the PFM was performed by comparing annual simulated patient flow data with actual patient flow data. Previously determined staffing scenarios were applied to the simulation and the resulting performance indicator outputs examined. RESULTS: The PFM was validated on model-wide and process-specific levels, with excellent validation observed on high acuity-patient length of stay and for highly detailed processes such as triage and registration. Simulation of the addition of a hospital volunteer and a second triage nurse demonstrated reductions in pretriage waiting time and the proportion of patients waiting longer than 30 or 60 minutes for pretriage. Simulation of an extra physician shift to the staff schedule demonstrated reductions in length of stay for patients of all triage categories. CONCLUSIONS: The PFM accurately represents patient flow through the department and can provide simulated patient flow information on a variety of scenarios. It can effectively simulate changes to the model and its effects on patient flow.

Appointments and Schedules↗
PubMed2006

Use of time by physiotherapists and occupational therapists in a stroke rehabilitation unit: a comparison between four European rehabilitation centres.

PURPOSE: The aim of this study was to compare the time allocated to therapeutic activities (TA) and non-therapeutic activities (NTA) of physiotherapists (PT) and occupational therapists (OT) in stroke rehabilitation units in four European countries. METHOD: Therapists documented their activities in 15-min periods for two weeks. They recorded: activity, number of patients, number of stroke patients, involvement of other people, location and frequency of each activity. Kruskal-Wallis tests and negative binomial regression models were used to compare activities between professional groups and between units. RESULTS: The average proportion of TA per day ranged between 32.9% and 66.1% and was higher for PT than for OT in each unit. For OT, significant differences emerged between the units in the proportion of time allocated to TA compared to NTA with British OTs spending significantly less time in TA. In the Belgian unit, three times less time was spent on patient-related co-ordination activities (e.g., administration, ward rounds) compared to the British and Swiss units. CONCLUSIONS: Time allocation differed between PT and OT and between units, affecting the time available for TA. Further investigation is necessary to study the effect of work organization in stroke rehabilitation units on the efficiency of rehabilitation regimes.

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